Visit my Google Scholar page here for a complete list of publications. * indicates a student author. † indicates corresponding author. + indicates co-first author.

Preprints

  • E.C. Hector†, L. Cella and R. Martin (2025+). Divide-and-conquer with finite sample sizes: valid and efficient possibilistic inference. arXiv, arXiv: 2503.22812. [arXiv], code. In review.
  • E.C. Hector† and A. Lenzi (2024+). When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer. arXiv, arXiv:2412.20323. [arXiv]. In review.
  • ​J. Hickey*, J.P. Williams, B.J. Reich and E.C. Hector (2024+). Multivariate and online transfer learning with uncertainty quantification. arXiv, arXiv:2411.12555. [arXiv]. In review.​​
  • W. Huang*, E.C. Hector, J. Cape and C. McKennan (2023+). A statistical framework for GWAS of high dimensional phenotypes using summary statistics, with application to metabolite GWAS. arXiv, arXiv: 2303.10221. [arXiv]. In review.​
  • H. Kim*, S.K. Ghosh, A. Di Martino and E.C. Hector (2023+). Bayesian estimation of clustered dependence structures in functional neuroconnectivity. arXiv, arXiv:2305.18044. [arXiv]. In review.
  • H. Kim*, S.K. Ghosh and E.C. Hector (2025+). A new block covariance regression model and inferential framework for massively large neuroimaging data. arXiv, arXiv:2502.21235. [arXiv]. In review.
  • R. Majumder, S. Fang, S. Arumugam, E.C. Hector and B.J. Reich (2024+). Conditional density estimation with neural networks for bias correction of multivariate climate model data. arXiv, arXiv:2411.18799. [arXiv]. In review.​​
  • C. Manschot* and E.C. Hector (2024+). Modeling massive physical activity monitor data through distributed inference. Preprint coming soon. In review. ​
  • E. Maceda*, E.C. Hector, A. Lenzi, B.J. Reich (2024+). A variational neural Bayes framework for inference on intractable posterior distributions. arXiv, arXiv:2404.10899. [arXiv], code. In review.
  • P. Segura, M. Pagani, S.L. Bishop, P. Thompson, S. Colcombe, T. Xu, Z.Z. Factor, E.C. Hector, S.H. Kim, M.V. Lombardo, A. Gozzi, X.F. Castellanos, C. Lord, M.P. Milham, A. Di Martino (2024+). Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder. medRxiv 2024.12.09.24318621. doi: 10.1101/2024.12.09.24318621. [medRxiv]. In review.

Peer-reviewed journal articles and book chapters

  • C. Manschot* and E.C. Hector (2025+). Functional regression with intensively measured longitudinal outcomes: a new lens through data partitioning. Accepted, to appear in The Canadian Journal of Statistics. [arXiv], code. 
  • ​​E.C. Hector†, B.J. Reich and A. Eloyan (2025). Distributed model building and recursive integration for big spatial data modeling.  Biometrics. 81(1):ujae159. Paper, [arXiv].​
  • E.C. Hector, D. Zhang, L. Tian, J. Feng, X. Yin, T. Xu, M. Laakso, Y. Bai, J. Xiao, J. Kang, T. Yu (2025). Dissecting genetic regulation of metabolic coordination. Briefings in Bioinformatics. 26(2):bbaf095. Paper, code.
  • E.C. Hector† and B.J. Reich (2024). Distributed inference for spatial extremes modeling in high dimensions. Journal of the American Statistical Association. 119(546):1297-1308. Paper, [arXiv], code. 
  • J. Hickey*, J.P. Williams and E.C. Hector (2024). Transfer learning with uncertainty quantification: Random Effect Calibration of Source to Target (RECaST). Journal of Machine Learning Research.​ 25(338):1-40. Paper, [arXiv], [researchers.one], code. 
  • A.N. Joignant*, E.C. Hector, M.M. Barnes, S.W. Kullman, D.C. Muddiman. Quantitative sampling by IR-MALDESI is not susceptible to tissue heterogeneity in multi-organ model. Analytical and Bioanalytical Chemistry. doi: 10.1007/s00216-024-05653-7. Paper. 
  • E.R. Bruce*, R.R.Kibbe*, E.C. Hector, D.C. Muddiman (2024). Absolute Quantification of Glutathione using Top-Hat Optics for IR-MALDESI Mass Spectrometry Imaging. Journal of Mass Spectrometry. 59(10):e5091. Paper.
  • E.C. Hector† and R. Martin (2024). Turning the information-sharing dial: efficient inference from different data sources. ​Electronic Journal of Statistics. 18(2):2974-3020. Paper, [arXiv], [researchers.one], code. 
  • E.C. Hector†, L. Tang, L. Zhou, P.X.-K. Song (2024). Data integration and model fusion in the Bayesian and Frequentist frameworks. Handbook on Bayesian, Fiducial and Frequentist Inference. Chapter 11 (pp. 238-263). Chapman and Hall/CRC Press. Chapter. 
  • A.L. Sohn*, R.R. Kibbe*, O.E. Dioli*, E.C. Hector, H. Bai, K.P. Garrard, D.C. Muddiman (2024). A statistical approach to System Suitability Testing (SST) for mass spectrometry imaging. Rapid Communications in Mass Spectrometry. 38(9):e9725. Paper. ​
  • E.C. Hector† (2023). Fused mean structure learning in data integration with dependence. The Canadian Journal of Statistics. 52(3):939-961. Paper, [arXiv].
  • A.A. Tagelsir, E.C. Hector, J.L .Urena-Cirett, A. Mercado-Garcia, A. Cantoral, H. Hu, K.E. Peterson, M.M. Téllez-Rojo, E.A. Martinez-Mier (2023). Early lead exposure is associated with molar incisor hypomineralization. Pediatric Dentistry. 45(5):427-433. Paper.
  • L. Luo, J. Wang and E.C. Hector† (2023). Rejoinder to Statistical inference for streamed longitudinal data. Biometrika. 110(4):841-858. Paper.
  • L. Luo, J. Wang and E.C. Hector† (2023). Statistical inference for streamed longitudinal data. Biometrika. 110(4):841-858. With discussion. Paper, [arXiv], code.
  • E.C. Hector†+, L. Luo+ and P.X.-K. Song (2023). Parallel-and-stream accelerator for computationally fast supervised learning. Computational Statistics and Data Analysis. 177:107587. Paper, [arXiv].
  • L. Shi*, M. Wank*, Y. Chen*, Y. Wang*, Y. Liu, E.C. Hector, P.X.-K. Song (2023). Sleep classification with artificial synthetic imaging data from empatica E4 wristband by convolutional neural networks. IEEE Journal of Biomedical and Health Informatics. 27(1):421-432. Paper, code.
  • E.C. Hector† and P.X.-K. Song (2022). Joint integrative analysis of multiple data sources with correlated vector outcomes. The Annals of Applied Statistics. 16(3):1700-1717. Paper, [arXiv], code.​​​
  • A.L. Sohn*, L. Ping, J.D. Glass, N.T. Seyfried, E.C. Hector, D.C. Muddiman (2022). Interrogating the Metabolomic Profile of Amyotrophic Lateral Sclerosis in the Post-Mortem Human Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry Imaging (MSI). Metabolites. 12(11):1096. Paper.
  • J. Twiddy*, E.C. Hector, V Dubljević (2022). Perceived invasiveness and therapeutic acceptability of transcranial magnetic stimulation. American Journal of Bioethics –Neuroscience. 14(1):17-20. Paper.
  • X. Yin, L.S. Chan, D. Bose, A.U. Jackson, P. VandeHaar, A.E. Locke, C. Fuchsberger, H.M. Stringham, K. Yu, L. Fernandes Silva, D. Zhang, E.C. Hector, E. Young, L. Ganel, I. Das, H.J. Abel, M.R. Erdos, L.L. Bonnycastle, J. Kuusisto, N.O. Stitziel, I. Hall, G.R. Wagner, J. Kang, J. Morrison, C.F. Burant, F.S. Collins, S. Ripatti, A. Palotie, N.B. Freimer, K.L. Mohlke, L. Scott, X. Wen, E. Fauman, M. Laakso, M. Boehnke (2022). Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci. Nature Communications. 13(1):1644. doi: 10.1038/s41467-022-29143-5. Paper.​
  • E.C. Hector† and P.X.-K. Song (2021). A distributed and integrated method of moments for high-dimensional correlated data analysis. Journal of the American Statistical Association. 116(534):805-818. Paper, [arXiv], code.
  • J.M. Goodrich, E.C. Hector, L. Tang, J.L. LaBarre, D.C. Dolinoy, A. Mercado-Garcia, A. Cantoral, P.X.-K. Song, M.M. Téllez-Rojo and K.E. Peterson (2020). Integrative analysis of gene-specific DNA methylation and untargeted metabolomics data from the ELEMENT cohort. Epigenetic Insights. 13:1-10. Paper.​
  • E.C. Hector† and P.X.-K. Song (2020). Doubly distributed supervised learning and inference with high-dimensional correlated outcomes. Journal of Machine Learning Research. 21:1–35. Paper, [arXiv], code.​
  • E.C. Jansen, E.C. Hector, J.M. Goodrich, A. Cantoral, M.M. Téllez Rojo, N. Basu, P.X.-K. Song, L. Torres Olascoaga, K.E. Peterson (2020). Mercury exposure in relation to sleep duration, timing, and fragmentation among adolescents in Mexico City. Environmental Research. 191:110216. Paper.
  • W. Perng, E.C. Hector, P.X.-K. Song, M.M. Téllez Rojo, S. Raskind, M. Kachman, A. Cantoral, B.F. Burant and K.E. Peterson (2017). Metabolomic determinants of metabolic risk in Mexican adolescents. Obesity. 25(9):1594-1602. Paper. ​​​

Invited comments

  • J. Wrobel, E.C. Hector, L. Crawford, L. D’Agostino McGowan, N. da Silva, J. Goldsmith, S. Hicks, M. Kane, Y. Lee, V. Mayrink, C.J. Paciorek, T. Usher, J. Wolfson a (2024). Partnering with authors to enhance reproducibility at JASA. Journal of the American Statistical Association. 119(546):795–797. Comment. ​
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a Authors after Hector are listed in alphabetical order to reflect equal contribution.